Overview

Dataset statistics

Number of variables15
Number of observations5694
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory711.8 KiB
Average record size in memory128.0 B

Variable types

Numeric15

Alerts

monetary is highly overall correlated with unique_prods and 6 other fieldsHigh correlation
unique_prods is highly overall correlated with monetary and 3 other fieldsHigh correlation
qt_prods is highly overall correlated with monetary and 4 other fieldsHigh correlation
avg_basket_size is highly overall correlated with unique_prods and 2 other fieldsHigh correlation
recency is highly overall correlated with relationship_duration and 3 other fieldsHigh correlation
relationship_duration is highly overall correlated with monetary and 6 other fieldsHigh correlation
purchase_count is highly overall correlated with monetary and 7 other fieldsHigh correlation
returns_count is highly overall correlated with relationship_duration and 3 other fieldsHigh correlation
monetary_returns is highly overall correlated with relationship_duration and 3 other fieldsHigh correlation
return_rate is highly overall correlated with returns_count and 1 other fieldsHigh correlation
avg_purchase_interval is highly overall correlated with monetary and 4 other fieldsHigh correlation
frequency is highly overall correlated with monetary and 4 other fieldsHigh correlation
avg_order_value is highly overall correlated with monetary and 3 other fieldsHigh correlation
monetary is highly skewed (γ1 = 23.01289978)Skewed
returns_count is highly skewed (γ1 = 30.34234755)Skewed
monetary_returns is highly skewed (γ1 = -35.41390123)Skewed
avg_unit_price is highly skewed (γ1 = 40.01799359)Skewed
return_rate is highly skewed (γ1 = 46.64019057)Skewed
avg_purchase_interval is highly skewed (γ1 = 67.66998836)Skewed
frequency is highly skewed (γ1 = 67.66998836)Skewed
avg_order_value is highly skewed (γ1 = 20.84922281)Skewed
customer_id has unique valuesUnique
relationship_duration has 2921 (51.3%) zerosZeros
returns_count has 4191 (73.6%) zerosZeros
monetary_returns has 4191 (73.6%) zerosZeros
return_rate has 4191 (73.6%) zerosZeros
avg_purchase_interval has 2921 (51.3%) zerosZeros
frequency has 2921 (51.3%) zerosZeros

Reproduction

Analysis started2023-06-28 10:42:34.444491
Analysis finished2023-06-28 10:43:09.130503
Duration34.69 seconds
Software versionydata-profiling vv4.2.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Distinct5694
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16601.346
Minimum12347
Maximum22709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:09.245419image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12700.65
Q114289.25
median16228
Q318210.75
95-th percentile21731.95
Maximum22709
Range10362
Interquartile range (IQR)3921.5

Descriptive statistics

Standard deviation2807.9223
Coefficient of variation (CV)0.16913823
Kurtosis-0.82113706
Mean16601.346
Median Absolute Deviation (MAD)1961.5
Skewness0.44131147
Sum94528065
Variance7884427.6
MonotonicityStrictly increasing
2023-06-28T07:43:09.448852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12347 1
 
< 0.1%
17596 1
 
< 0.1%
17562 1
 
< 0.1%
17561 1
 
< 0.1%
17560 1
 
< 0.1%
17557 1
 
< 0.1%
17556 1
 
< 0.1%
17555 1
 
< 0.1%
17554 1
 
< 0.1%
17553 1
 
< 0.1%
Other values (5684) 5684
99.8%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12349 1
< 0.1%
12350 1
< 0.1%
12352 1
< 0.1%
12353 1
< 0.1%
12354 1
< 0.1%
12355 1
< 0.1%
12356 1
< 0.1%
12357 1
< 0.1%
ValueCountFrequency (%)
22709 1
< 0.1%
22708 1
< 0.1%
22707 1
< 0.1%
22706 1
< 0.1%
22705 1
< 0.1%
22704 1
< 0.1%
22700 1
< 0.1%
22699 1
< 0.1%
22696 1
< 0.1%
22695 1
< 0.1%

monetary
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5448
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1761.0598
Minimum0.42
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:09.640205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.42
5-th percentile13.1495
Q1236.1125
median612.99
Q31570.115
95-th percentile5301.6895
Maximum279138.02
Range279137.6
Interquartile range (IQR)1334.0025

Descriptive statistics

Standard deviation7516.7119
Coefficient of variation (CV)4.2682887
Kurtosis698.08417
Mean1761.0598
Median Absolute Deviation (MAD)479.175
Skewness23.0129
Sum10027475
Variance56500957
MonotonicityNot monotonic
2023-06-28T07:43:09.823184image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.95 9
 
0.2%
4.95 8
 
0.1%
1.25 8
 
0.1%
2.95 8
 
0.1%
1.65 7
 
0.1%
3.75 7
 
0.1%
12.75 7
 
0.1%
7.5 6
 
0.1%
5.95 6
 
0.1%
4.25 6
 
0.1%
Other values (5438) 5622
98.7%
ValueCountFrequency (%)
0.42 1
 
< 0.1%
0.65 1
 
< 0.1%
0.79 1
 
< 0.1%
0.84 4
0.1%
0.85 3
 
0.1%
1.07 1
 
< 0.1%
1.25 8
0.1%
1.44 1
 
< 0.1%
1.65 7
0.1%
1.69 1
 
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65039.62 1
< 0.1%

unique_prods
Real number (ℝ)

Distinct439
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.681595
Minimum1
Maximum1786
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:10.096100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q113
median36
Q384.75
95-th percentile241.35
Maximum1786
Range1785
Interquartile range (IQR)71.75

Descriptive statistics

Standard deviation101.73535
Coefficient of variation (CV)1.4600032
Kurtosis43.87754
Mean69.681595
Median Absolute Deviation (MAD)28
Skewness4.703277
Sum396767
Variance10350.081
MonotonicityNot monotonic
2023-06-28T07:43:10.309845image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 278
 
4.9%
2 149
 
2.6%
3 112
 
2.0%
10 101
 
1.8%
5 98
 
1.7%
9 96
 
1.7%
6 93
 
1.6%
8 93
 
1.6%
11 92
 
1.6%
4 90
 
1.6%
Other values (429) 4492
78.9%
ValueCountFrequency (%)
1 278
4.9%
2 149
2.6%
3 112
2.0%
4 90
 
1.6%
5 98
 
1.7%
6 93
 
1.6%
7 90
 
1.6%
8 93
 
1.6%
9 96
 
1.7%
10 101
 
1.8%
ValueCountFrequency (%)
1786 1
< 0.1%
1766 1
< 0.1%
1322 1
< 0.1%
1118 1
< 0.1%
1109 1
< 0.1%
884 1
< 0.1%
817 1
< 0.1%
748 1
< 0.1%
730 1
< 0.1%
720 1
< 0.1%

qt_prods
Real number (ℝ)

Distinct529
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.625571
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:10.533872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114
median41
Q3106
95-th percentile332.35
Maximum7838
Range7837
Interquartile range (IQR)92

Descriptive statistics

Standard deviation210.59359
Coefficient of variation (CV)2.273601
Kurtosis510.23293
Mean92.625571
Median Absolute Deviation (MAD)33
Skewness17.752506
Sum527410
Variance44349.661
MonotonicityNot monotonic
2023-06-28T07:43:10.773981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 255
 
4.5%
2 149
 
2.6%
3 108
 
1.9%
10 101
 
1.8%
6 99
 
1.7%
9 92
 
1.6%
5 91
 
1.6%
4 87
 
1.5%
7 83
 
1.5%
11 83
 
1.5%
Other values (519) 4546
79.8%
ValueCountFrequency (%)
1 255
4.5%
2 149
2.6%
3 108
1.9%
4 87
 
1.5%
5 91
 
1.6%
6 99
 
1.7%
7 83
 
1.5%
8 81
 
1.4%
9 92
 
1.6%
10 101
 
1.8%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_basket_size
Real number (ℝ)

Distinct1255
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.991481
Minimum1
Maximum1113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:11.090341image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.3333333
Q19
median18
Q335.6125
95-th percentile175.35
Maximum1113
Range1112
Interquartile range (IQR)26.6125

Descriptive statistics

Standard deviation77.016374
Coefficient of variation (CV)1.9258195
Kurtosis32.294916
Mean39.991481
Median Absolute Deviation (MAD)11.267857
Skewness4.9956284
Sum227711.5
Variance5931.5219
MonotonicityNot monotonic
2023-06-28T07:43:11.347534image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 282
 
5.0%
2 160
 
2.8%
3 116
 
2.0%
13 108
 
1.9%
10 103
 
1.8%
9 99
 
1.7%
6 95
 
1.7%
5 94
 
1.7%
4 92
 
1.6%
11 91
 
1.6%
Other values (1245) 4454
78.2%
ValueCountFrequency (%)
1 282
5.0%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1.5 7
 
0.1%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 160
2.8%
ValueCountFrequency (%)
1113 1
< 0.1%
748 1
< 0.1%
730 1
< 0.1%
720 1
< 0.1%
704 1
< 0.1%
686 1
< 0.1%
675 1
< 0.1%
674 1
< 0.1%
661 1
< 0.1%
650 1
< 0.1%

recency
Real number (ℝ)

Distinct304
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean116.89111
Minimum0
Maximum373
Zeros37
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:11.633471image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q123
median71
Q3200
95-th percentile338
Maximum373
Range373
Interquartile range (IQR)177

Descriptive statistics

Standard deviation111.6221
Coefficient of variation (CV)0.95492377
Kurtosis-0.64121555
Mean116.89111
Median Absolute Deviation (MAD)61
Skewness0.81483305
Sum665578
Variance12459.494
MonotonicityNot monotonic
2023-06-28T07:43:11.881951image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 110
 
1.9%
4 105
 
1.8%
3 98
 
1.7%
2 92
 
1.6%
10 86
 
1.5%
8 82
 
1.4%
9 79
 
1.4%
17 79
 
1.4%
7 78
 
1.4%
15 66
 
1.2%
Other values (294) 4819
84.6%
ValueCountFrequency (%)
0 37
 
0.6%
1 110
1.9%
2 92
1.6%
3 98
1.7%
4 105
1.8%
5 52
0.9%
7 78
1.4%
8 82
1.4%
9 79
1.4%
10 86
1.5%
ValueCountFrequency (%)
373 23
0.4%
372 23
0.4%
371 17
0.3%
369 4
 
0.1%
368 13
0.2%
367 16
0.3%
366 15
0.3%
365 19
0.3%
364 11
0.2%
362 7
 
0.1%

relationship_duration
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct374
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.368282
Minimum0
Maximum373
Zeros2921
Zeros (%)51.3%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:12.076269image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3207
95-th percentile353
Maximum373
Range373
Interquartile range (IQR)207

Descriptive statistics

Standard deviation128.15686
Coefficient of variation (CV)1.289716
Kurtosis-0.80706617
Mean99.368282
Median Absolute Deviation (MAD)0
Skewness0.87305506
Sum565803
Variance16424.181
MonotonicityNot monotonic
2023-06-28T07:43:12.263072image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2921
51.3%
364 28
 
0.5%
350 26
 
0.5%
357 25
 
0.4%
366 20
 
0.4%
351 20
 
0.4%
355 19
 
0.3%
365 18
 
0.3%
343 18
 
0.3%
356 17
 
0.3%
Other values (364) 2582
45.3%
ValueCountFrequency (%)
0 2921
51.3%
1 9
 
0.2%
2 4
 
0.1%
3 5
 
0.1%
4 4
 
0.1%
5 3
 
0.1%
6 2
 
< 0.1%
7 7
 
0.1%
8 5
 
0.1%
9 3
 
0.1%
ValueCountFrequency (%)
373 5
 
0.1%
372 8
 
0.1%
371 8
 
0.1%
370 8
 
0.1%
369 6
 
0.1%
368 10
 
0.2%
367 11
 
0.2%
366 20
0.4%
365 18
0.3%
364 28
0.5%

purchase_count
Real number (ℝ)

Distinct56
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4717246
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:12.473450image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q34
95-th percentile11
Maximum206
Range205
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.8138139
Coefficient of variation (CV)1.9626597
Kurtosis302.04793
Mean3.4717246
Median Absolute Deviation (MAD)0
Skewness13.1919
Sum19768
Variance46.42806
MonotonicityNot monotonic
2023-06-28T07:43:12.651493image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 2870
50.4%
2 825
 
14.5%
3 503
 
8.8%
4 394
 
6.9%
5 237
 
4.2%
6 173
 
3.0%
7 138
 
2.4%
8 98
 
1.7%
9 69
 
1.2%
10 55
 
1.0%
Other values (46) 332
 
5.8%
ValueCountFrequency (%)
1 2870
50.4%
2 825
 
14.5%
3 503
 
8.8%
4 394
 
6.9%
5 237
 
4.2%
6 173
 
3.0%
7 138
 
2.4%
8 98
 
1.7%
9 69
 
1.2%
10 55
 
1.0%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
< 0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
< 0.1%
60 1
< 0.1%
57 1
< 0.1%

returns_count
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct213
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.239902
Minimum0
Maximum9014
Zeros4191
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:12.875476image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile38
Maximum9014
Range9014
Interquartile range (IQR)1

Descriptive statistics

Standard deviation204.94904
Coefficient of variation (CV)11.236302
Kurtosis1138.869
Mean18.239902
Median Absolute Deviation (MAD)0
Skewness30.342348
Sum103858
Variance42004.11
MonotonicityNot monotonic
2023-06-28T07:43:13.056036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
73.6%
1 169
 
3.0%
2 150
 
2.6%
3 105
 
1.8%
4 89
 
1.6%
6 78
 
1.4%
5 61
 
1.1%
12 52
 
0.9%
7 44
 
0.8%
8 43
 
0.8%
Other values (203) 712
 
12.5%
ValueCountFrequency (%)
0 4191
73.6%
1 169
 
3.0%
2 150
 
2.6%
3 105
 
1.8%
4 89
 
1.6%
5 61
 
1.1%
6 78
 
1.4%
7 44
 
0.8%
8 43
 
0.8%
9 41
 
0.7%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

monetary_returns
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1085
Distinct (%)19.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-39.585478
Minimum-22998.4
Maximum0
Zeros4191
Zeros (%)73.6%
Negative1503
Negative (%)26.4%
Memory size89.0 KiB
2023-06-28T07:43:13.231442image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum-22998.4
5-th percentile-105.839
Q1-3.75
median0
Q30
95-th percentile0
Maximum0
Range22998.4
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation438.66008
Coefficient of variation (CV)-11.081339
Kurtosis1588.7212
Mean-39.585478
Median Absolute Deviation (MAD)0
Skewness-35.413901
Sum-225399.71
Variance192422.67
MonotonicityNot monotonic
2023-06-28T07:43:13.414214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
73.6%
-12.75 20
 
0.4%
-4.95 19
 
0.3%
-15 17
 
0.3%
-9.95 17
 
0.3%
-5.9 12
 
0.2%
-25.5 11
 
0.2%
-4.25 10
 
0.2%
-3.75 9
 
0.2%
-19.9 8
 
0.1%
Other values (1075) 1380
 
24.2%
ValueCountFrequency (%)
-22998.4 1
< 0.1%
-14688.24 1
< 0.1%
-8511.15 1
< 0.1%
-7443.59 1
< 0.1%
-5228.4 1
< 0.1%
-4815.26 1
< 0.1%
-4814.74 1
< 0.1%
-4486.24 1
< 0.1%
-4429 1
< 0.1%
-3677.15 1
< 0.1%
ValueCountFrequency (%)
0 4191
73.6%
-0.42 2
 
< 0.1%
-0.65 1
 
< 0.1%
-0.95 1
 
< 0.1%
-1.25 4
 
0.1%
-1.45 4
 
0.1%
-1.64 1
 
< 0.1%
-1.65 5
 
0.1%
-1.7 2
 
< 0.1%
-1.79 1
 
< 0.1%

avg_unit_price
Real number (ℝ)

Distinct5265
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7161781
Minimum0.06
Maximum434.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:13.596914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile1.2516557
Q12.2178856
median3.0488988
Q34.25
95-th percentile6.6996959
Maximum434.65
Range434.59
Interquartile range (IQR)2.0321144

Descriptive statistics

Standard deviation7.8496708
Coefficient of variation (CV)2.1122967
Kurtosis1952.5571
Mean3.7161781
Median Absolute Deviation (MAD)0.95889881
Skewness40.017994
Sum21159.918
Variance61.617331
MonotonicityNot monotonic
2023-06-28T07:43:13.805557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.25 26
 
0.5%
4.95 20
 
0.4%
0.85 18
 
0.3%
3.75 16
 
0.3%
2.95 15
 
0.3%
1.65 14
 
0.2%
0.42 13
 
0.2%
2.08 13
 
0.2%
12.75 12
 
0.2%
2.55 12
 
0.2%
Other values (5255) 5535
97.2%
ValueCountFrequency (%)
0.06 1
< 0.1%
0.1225 1
< 0.1%
0.17 2
< 0.1%
0.2327777778 1
< 0.1%
0.29 2
< 0.1%
0.32 1
< 0.1%
0.33 1
< 0.1%
0.355 2
< 0.1%
0.358 1
< 0.1%
0.3666666667 1
< 0.1%
ValueCountFrequency (%)
434.65 1
< 0.1%
295 1
< 0.1%
125 1
< 0.1%
110 2
< 0.1%
74.975 1
< 0.1%
66.475 1
< 0.1%
59.73333333 1
< 0.1%
54.3 1
< 0.1%
51.71 1
< 0.1%
39.95 1
< 0.1%

return_rate
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct471
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5632628
Minimum0
Maximum3004.6667
Zeros4191
Zeros (%)73.6%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:14.014174image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.22222222
95-th percentile7.5
Maximum3004.6667
Range3004.6667
Interquartile range (IQR)0.22222222

Descriptive statistics

Standard deviation48.566706
Coefficient of variation (CV)13.629841
Kurtosis2669.7275
Mean3.5632628
Median Absolute Deviation (MAD)0
Skewness46.640191
Sum20289.219
Variance2358.7249
MonotonicityNot monotonic
2023-06-28T07:43:14.225667image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4191
73.6%
1 112
 
2.0%
2 81
 
1.4%
0.5 64
 
1.1%
3 52
 
0.9%
0.3333333333 43
 
0.8%
4 40
 
0.7%
1.5 33
 
0.6%
6 32
 
0.6%
0.25 29
 
0.5%
Other values (461) 1017
 
17.9%
ValueCountFrequency (%)
0 4191
73.6%
0.03571428571 1
 
< 0.1%
0.04761904762 1
 
< 0.1%
0.05 1
 
< 0.1%
0.05555555556 1
 
< 0.1%
0.07272727273 1
 
< 0.1%
0.07692307692 1
 
< 0.1%
0.08333333333 1
 
< 0.1%
0.09090909091 2
 
< 0.1%
0.1 6
 
0.1%
ValueCountFrequency (%)
3004.666667 1
< 0.1%
1228 1
< 0.1%
1006 1
< 0.1%
510 1
< 0.1%
426 1
< 0.1%
378.75 1
< 0.1%
336 1
< 0.1%
314 1
< 0.1%
312 1
< 0.1%
300 1
< 0.1%

avg_purchase_interval
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1229
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.030117058
Minimum0
Maximum34
Zeros2921
Zeros (%)51.3%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:14.445400image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.023952096
95-th percentile0.076923077
Maximum34
Range34
Interquartile range (IQR)0.023952096

Descriptive statistics

Standard deviation0.46823463
Coefficient of variation (CV)15.547157
Kurtosis4874.1687
Mean0.030117058
Median Absolute Deviation (MAD)0
Skewness67.669988
Sum171.48653
Variance0.21924367
MonotonicityNot monotonic
2023-06-28T07:43:14.623724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2921
51.3%
0.07142857143 16
 
0.3%
0.04761904762 15
 
0.3%
0.02857142857 14
 
0.2%
0.0303030303 14
 
0.2%
0.01587301587 14
 
0.2%
0.06451612903 13
 
0.2%
0.02380952381 13
 
0.2%
0.1428571429 13
 
0.2%
0.025 12
 
0.2%
Other values (1219) 2649
46.5%
ValueCountFrequency (%)
0 2921
51.3%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005602240896 2
 
< 0.1%
0.005617977528 1
 
< 0.1%
0.005633802817 2
 
< 0.1%
0.005681818182 1
 
< 0.1%
0.005698005698 2
 
< 0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 6
0.1%
1.5 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1 4
0.1%
0.6666666667 3
0.1%
0.5522788204 1
 
< 0.1%
0.5349462366 1
 
< 0.1%

frequency
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1229
Distinct (%)21.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.030117058
Minimum0
Maximum34
Zeros2921
Zeros (%)51.3%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:14.804957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.023952096
95-th percentile0.076923077
Maximum34
Range34
Interquartile range (IQR)0.023952096

Descriptive statistics

Standard deviation0.46823463
Coefficient of variation (CV)15.547157
Kurtosis4874.1687
Mean0.030117058
Median Absolute Deviation (MAD)0
Skewness67.669988
Sum171.48653
Variance0.21924367
MonotonicityNot monotonic
2023-06-28T07:43:14.978047image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2921
51.3%
0.07142857143 16
 
0.3%
0.04761904762 15
 
0.3%
0.02857142857 14
 
0.2%
0.0303030303 14
 
0.2%
0.01587301587 14
 
0.2%
0.06451612903 13
 
0.2%
0.02380952381 13
 
0.2%
0.1428571429 13
 
0.2%
0.025 12
 
0.2%
Other values (1219) 2649
46.5%
ValueCountFrequency (%)
0 2921
51.3%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005602240896 2
 
< 0.1%
0.005617977528 1
 
< 0.1%
0.005633802817 2
 
< 0.1%
0.005681818182 1
 
< 0.1%
0.005698005698 2
 
< 0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
6 1
 
< 0.1%
4 1
 
< 0.1%
2 6
0.1%
1.5 1
 
< 0.1%
1.333333333 2
 
< 0.1%
1 4
0.1%
0.6666666667 3
0.1%
0.5522788204 1
 
< 0.1%
0.5349462366 1
 
< 0.1%

avg_order_value
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct5453
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean553.84456
Minimum0.42
Maximum52940.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size89.0 KiB
2023-06-28T07:43:15.167327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0.42
5-th percentile12.8325
Q1158.875
median296.99643
Q3486.30437
95-th percentile1840.0245
Maximum52940.94
Range52940.52
Interquartile range (IQR)327.42937

Descriptive statistics

Standard deviation1380.1967
Coefficient of variation (CV)2.492029
Kurtosis694.08971
Mean553.84456
Median Absolute Deviation (MAD)151.99893
Skewness20.849223
Sum3153590.9
Variance1904943
MonotonicityNot monotonic
2023-06-28T07:43:15.349715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.95 9
 
0.2%
2.95 8
 
0.1%
4.95 8
 
0.1%
1.25 8
 
0.1%
12.75 7
 
0.1%
1.65 7
 
0.1%
3.75 7
 
0.1%
7.5 6
 
0.1%
5.95 6
 
0.1%
4.25 6
 
0.1%
Other values (5443) 5622
98.7%
ValueCountFrequency (%)
0.42 1
 
< 0.1%
0.65 1
 
< 0.1%
0.79 1
 
< 0.1%
0.84 4
0.1%
0.85 3
 
0.1%
1.07 1
 
< 0.1%
1.25 8
0.1%
1.44 1
 
< 0.1%
1.65 7
0.1%
1.69 1
 
< 0.1%
ValueCountFrequency (%)
52940.94 1
< 0.1%
50653.91 1
< 0.1%
21389.6 1
< 0.1%
18745.86 1
< 0.1%
14855.53 1
< 0.1%
14844.76667 1
< 0.1%
13305.5 1
< 0.1%
12681.58 1
< 0.1%
12633.67 1
< 0.1%
12172.09 1
< 0.1%

Interactions

2023-06-28T07:43:06.332062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:34.818266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:37.043046image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.361441image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.638654image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.915746image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.031200image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.304729image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.523281image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:53.089922image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.399836image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.501110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.567429image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.722037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.030291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:06.513268image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:34.951472image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:37.219875image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.507485image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.797313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.053550image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.174230image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.447763image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.656945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:53.237247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.542877image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.636049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.706387image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.862829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.173413image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:06.660065image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:35.086563image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:37.378272image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.649648image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.948351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.202832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.319071image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.588719image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.793480image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:53.391919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.681405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.771891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.845573image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.004551image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.324957image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:06.816832image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:35.225981image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:37.545166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.802459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:42.108308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.349872image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.467568image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.740238image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.947402image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:53.551455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.830520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.916425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.994244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.152340image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.508916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:06.984385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:35.395431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:37.711959image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.963449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:42.272196image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.499176image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.623606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.923586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:51.097849image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:53.719645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.979841image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.064050image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:00.157374image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.307037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.681470image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.127382image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:35.536469image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:37.859687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:40.130368image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:42.424670image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.629840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.796948image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.063514image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:51.257814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:53.874920image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.112149image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.216247image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:00.295412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.449886image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.823912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.283769image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:35.716345image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.021425image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:40.284264image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:42.575978image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.776747image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:46.977608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.210221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:51.412791image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.037302image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.255477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.359939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:00.440252image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.661313image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:04.971143image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.452301image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:35.870095image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.184181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:40.436410image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:42.739360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:44.926594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:47.143234image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.357004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:51.563449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.201798image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.398263image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.500449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:00.593237image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.820048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:05.122080image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.585898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.007254image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.326947image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:40.571882image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:42.877524image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.063169image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:47.279790image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.493501image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:51.952327image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.341336image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.526248image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.627939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:00.728463image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:02.961156image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:05.260416image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.718528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.163421image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.466372image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:40.717351image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.015783image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.198296image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:47.412208image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.628601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:52.105058image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.484523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.674912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.762043image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:00.863405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:03.113289image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:05.397370image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.851166image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.297685image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.609141image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:40.866205image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.156888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.328185image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:47.545789image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.770099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:52.259448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.626840image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.804164image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:58.890275image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.004631image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:03.260392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:05.531810image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:07.984159image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.429749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.752148image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.014352image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.296242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.461294image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:47.679547image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:49.903433image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:52.418902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.782503image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:56.932639image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.013365image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.141502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:03.409969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:05.710528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:08.126891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.582523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:38.906018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.171385image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.443303image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.603945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:47.844723image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.082626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:52.596266image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:54.936457image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.073998image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.154894image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.285976image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:03.566928image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:05.869794image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:08.296712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.742111image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.060005image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.325829image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.600048image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.751528image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.007461image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.232121image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:52.776229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.094638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.221490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.298384image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.438326image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:03.735914image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:06.025177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:08.443068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:36.896427image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:39.214742image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:41.483814image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:43.766916image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:45.894153image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:48.159878image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:50.384431image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:52.934716image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:55.250082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:57.364865image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:42:59.437201image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:01.582702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:03.887800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-06-28T07:43:06.172355image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-06-28T07:43:15.508724image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countmonetary_returnsavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
customer_id1.000-0.180-0.017-0.0490.1130.245-0.382-0.383-0.2770.2750.216-0.278-0.381-0.381-0.039
monetary-0.1801.0000.7960.8370.489-0.4270.6000.6440.433-0.4330.0780.3990.5490.5490.765
unique_prods-0.0170.7961.0000.9880.823-0.3270.4230.4500.271-0.2710.0630.2410.3650.3650.640
qt_prods-0.0490.8370.9881.0000.768-0.3790.4970.5330.317-0.3170.0380.2820.4380.4380.626
avg_basket_size0.1130.4890.8230.7681.000-0.038-0.038-0.047-0.0210.0220.123-0.021-0.064-0.0640.678
recency0.245-0.427-0.327-0.379-0.0381.000-0.598-0.597-0.3210.3200.203-0.292-0.519-0.519-0.085
relationship_duration-0.3820.6000.4230.497-0.038-0.5981.0000.9450.503-0.503-0.1620.4670.8160.8160.074
purchase_count-0.3830.6440.4500.533-0.047-0.5970.9451.0000.539-0.539-0.1660.4970.9020.9020.076
returns_count-0.2770.4330.2710.317-0.021-0.3210.5030.5391.000-0.994-0.0610.9940.4650.4650.155
monetary_returns0.275-0.433-0.271-0.3170.0220.320-0.503-0.539-0.9941.0000.043-0.988-0.466-0.466-0.154
avg_unit_price0.2160.0780.0630.0380.1230.203-0.162-0.166-0.0610.0431.000-0.058-0.162-0.1620.204
return_rate-0.2780.3990.2410.282-0.021-0.2920.4670.4970.994-0.988-0.0581.0000.4330.4330.153
avg_purchase_interval-0.3810.5490.3650.438-0.064-0.5190.8160.9020.465-0.466-0.1620.4331.0001.0000.059
frequency-0.3810.5490.3650.438-0.064-0.5190.8160.9020.465-0.466-0.1620.4331.0001.0000.059
avg_order_value-0.0390.7650.6400.6260.678-0.0850.0740.0760.155-0.1540.2040.1530.0590.0591.000

Missing values

2023-06-28T07:43:08.667405image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-06-28T07:43:08.989962image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countmonetary_returnsavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
012347.04310.0010318226.000000236570.00.002.6440110.00.0191780.019178615.714286
112348.01437.2421276.7500007528340.00.000.6929630.00.0141340.014134359.310000
212349.01457.55727272.00000018010.00.004.2375000.00.0000000.0000001457.550000
312350.0294.40161616.000000310010.00.001.5812500.00.0000000.000000294.400000
412352.01385.74577711.00000036260763.0-120.334.0754559.00.0269230.026923197.962857
512353.089.00444.000000204010.00.006.0750000.00.0000000.00000089.000000
612354.01079.40585858.000000232010.00.004.5037930.00.0000000.0000001079.400000
712355.0459.40131313.000000214010.00.004.2038460.00.0000000.000000459.400000
812356.02487.43525819.3333332230330.00.002.9460340.00.0099010.009901829.143333
912357.06207.67131131131.00000033010.00.003.3486260.00.0000000.0000006207.670000
customer_idmonetaryunique_prodsqt_prodsavg_basket_sizerecencyrelationship_durationpurchase_countreturns_countmonetary_returnsavg_unit_pricereturn_rateavg_purchase_intervalfrequencyavg_order_value
568422695.06083.95675675675.01010.00.04.2560740.00.00.06083.95
568522696.07150.07748748748.01010.00.04.2925940.00.00.07150.07
568622699.03686.80203203203.01010.00.05.7723150.00.00.03686.80
568722700.04839.42556262.01010.00.07.2545160.00.00.04839.42
568822704.017.90777.01010.00.01.2785710.00.00.017.90
568922705.03.35222.01010.00.01.6750000.00.00.03.35
569022706.05699.00634634634.01010.00.04.3209460.00.00.05699.00
569122707.06756.06730730730.00010.00.04.1759040.00.00.06756.06
569222708.03217.20565959.00010.00.06.2696610.00.00.03217.20
569322709.03950.72217217217.00010.00.06.3643780.00.00.03950.72